Chemists at the University of Münster, led by Prof Frank Glorius, have developed a new strategy for assessing the applicability of chemical reactions. The team has proposed a computer-aided, bias-free method for selecting model substrates to evaluate new chemical reactions, aiming to improve the quality and information content of chemical reaction data and close knowledge gaps.

Chemists often develop and optimize new chemical reactions using model systems and demonstrate the versatile applicability, referred to as ‘scope’ in technical jargon, using a selection of substrates. However, this subjective selection often results in a distorted picture of the range of applications of the newly developed reaction, making it unclear whether it can be used to synthesize a desired product.

The team’s method is based on the complexity and structural properties of real pharmaceutical compounds, with the goal of lowering the barriers to the application of new reactions in both academic and industrial contexts. The availability of high-quality, unbiased data also significantly facilitates the use of machine learning and paves the way for a more comprehensive use of the data.

The work, published in the journal ACS Central Science, aims to initiate a ‘rethinking process’ in the evaluation of chemical reactions. Instead of focusing on biased or predictably outcome experiments, the team advocates for obtaining the best possible data about new chemical reactions.

Unlike previous work, the method presented by the Münster team takes the entire structure of a molecule into account, aiming to provide a more comprehensive and unbiased evaluation of chemical reactions. The team’s approach represents an important step towards standardizing and objectifying the development and evaluation of chemical reactions, with potential implications for the future of chemical research and application.